In order to monitor the status of a technical system while in operation and to generate diagnostics relating to the behavior of the power station components, a plurality of technical variables (for example pressure, temperature and flow) are generally recorded by means of sensors and the measured values achieved thereby are evaluated.
However, knowledge of these measured values alone is generally insufficient in order to be able to evaluate the status of a technical system, with the consequence that the captured data must be supplied to a further processing facility. In this process characteristic variables, for example, are determined which possess a substantially higher, and more often than not, explicit significance compared with the raw measured values, thus providing a basis to enable selective monitoring and diagnosis of the technical system.
A known method for further data analysis of the captured data is to use a control device which controls the data processing in its entirety. However, this control device must monitor the execution of the multistage data processing from beginning to end. In each of the individual stages of the data processing, the captured data is subjected to a specific analysis in a fixed sequence and a characteristic variable, for example, is determined at each stage. In the event that an error occurs during this data processing in one of the stages or in the control device itself, whether as a result of the fact that the data analysis was designed incorrectly or because the technical system or its measured value acquisition is in a state for which the data analysis was previously not designed, the control device usually aborts the data processing.
It is then generally very difficult to determine at which point in the data processing a search for the error should be initiated, with the result that the monitoring and diagnostics system or even the technical system itself must often be switched off during troubleshooting. If the monitoring system is switched off during troubleshooting, data accumulated during this downtime will not be longer available subsequently for, say, a long-term analysis of the behavior of the technical system, which in turn reduces the accuracy of the monitoring and diagnosis.